DBMS > AnzoGraph DB vs. Citus vs. MySQL vs. OrientDB vs. SAP IQ

System Properties Comparison AnzoGraph DB vs. Citus vs. MySQL vs. OrientDB vs. SAP IQ

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Widely used open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Columnar RDBMS optimized for Big Data analytics

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Relational DBMS

column-oriented

Secondary database models

Document store

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	2.64
Rank	#108	Overall
	#52	Relational DBMS

Website

cambridgesemantics.com/anzograph

www.citusdata.com

www.mysql.com

orientdb.org

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.citusdata.com

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

help.sap.com/docs/SAP_IQ

Developer

Cambridge Semantics

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

SAP, formerly Sybase

Initial release

2018

2010

1995

2010

1994

Current release

2.3, January 2021

8.1, December 2018

8.4.0, April 2024

3.2.29, March 2024

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

free trial version available

Open Source

AGPL, commercial license also available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

C and C++

Java

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

standard, with numerous extensions

yes

with proprietary extensions

SQL-like query language, no joins

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

proprietary syntax

Java, Javascript

yes

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication
Source-replica replication

Multi-source replication

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

could be achieved with distributed queries

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

not for MyISAM storage engine

yes

relationship in graphs

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

fine grained access rights according to SQL-standard

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